The present invention relates redundance reduction method used in coding of signals and further relates to a device for decoding redundance-reduced signals.
German Patent 43 20 990 A1 describes a redundance reduction method used in coding multichannel signals. In particular, the coding of dual-channel audio signals is described. For the purpose of redundance reduction, the signals are sampled, quantized, and predictively coded in an encoder. Estimated values for the actual sampled values are obtained. The prediction error is determined and loaded for transmission over a data line. The predictive coding is an adaptive interchannel prediction, i.e., use is made of the statistical relationship between the signals in the two channels (cross-correlation). The predictor coefficients must be transmitted to the receiver as lateral information.
U.S. Pat. No. 4,815,132 describes a redundance reduction method used in coding dual-channel signals that are available in digitized form. The digitized signals are predictively coded, and a prediction error between the digitized and predictively coded signals is determined. The prediction error values are quantized and loaded for transmission over a transmission path. Linear backward-adaptive prediction is performed for two channels simultaneously, with the statistical relationships within a channel and between two channels taken into account. Furthermore, U.S. Pat. No. 4,815,132 describes the use of a linear backward-adaptive predictor that receives the quantized prediction values of two channels.
WO A-9016136 discloses predictors with a lattice-type structure.
A backward-adaptive predictor for the case of a single channel is described in N. S. Jayant, P. Noll, xe2x80x9cDigital coding of waveforms,xe2x80x9d Prentice-Hall, Englewood, N.J., 1984.
In P. Cambridge, M. Todd, xe2x80x9cAudio Data Compression Techniques,xe2x80x9d 94th AES Convention, Preprint 3584 (K1-9), Berlin, March 1993, the possibility of using auto-correlations and cross-correlations for a predictor for two stereo channels is mentioned. No specific implementation is suggested, however.
The method according to the present invention provides the advantage that coding is not degraded by prediction. Another advantage is that linear and backward-adaptive prediction is carried out jointly for at least two channels; the statistical linkages are made use of not only between the channels, but are also taken into account within each individual channel. Thus it is achieved that the quality of the prediction is improved and a higher prediction gain is made possible in many signal ranges. For example, in coding audio signals with a data rate of 64 kbit/s, the quality of the transmitted signals can be significantly improved.
The present invention relates to predictors in general for the case of N channels; i.e., more than one channel can be predicted at a time, making use of the statistical linkages both within a single channel (auto-correlations) and between the channels (cross-correlations). A clear prediction gain is thus achieved in comparison with the single-channel case, where only autocorrelation is used.
By performing backward-adaptive prediction, the predictor coefficients may be calculated from the values already transmitted, so that the predictor coefficients do not need to be transmitted. This is not possible in the case of forward-adaptive predictors, where the predictor coefficients would also have to be transmitted to the receiver, which would result in increased data transmission load.
The present invention provides the advantage that signal prediction may be performed in stages with a lattice-type structure used for each predictor stage. This results in an orthogonal system being formed, at least in the case of steady-state signals, which allows for simple variation of the order of the predictors, since adding a stage to the existing stages does not affect the previous stages. Therefore the optimum predictor from the point of view of computer load and prediction quality may be selected in each specific case.
In order to adaptively compute the predictor coefficients, the sum of error signal intensities is determined in the at least two channels. For this purpose, the expectation values for the error signals in the at least two channels are needed. It is advantageous if the expectation values are replaced by mean values over a certain signal history period. The computer load is significantly reduced in this manner.
It is also advantageous when individual predictor stages are designed so that they can be switched off. This allows the predictor to react flexibly if, for example, instability occurs in a prediction. In backward-adaptive systems, this may occur, for example, if the signal statistics are changed due to a signal change.
It is also advantageous when the stages that have been switched off continue to operate as backward-adaptive predictors in the forward feed direction. Thus it is achieved that the predictor coefficients even of the stages that have been turned off are further adapted, so that when those stages are switched on again, the corresponding predictor coefficients do not need to be adapted completely anew.
Furthermore, it is advantageous when use is also made of the statistical relationships between simultaneous sampling values in at least two channels (cross-correlations). For this purpose, a simple zero-order inter-channel predictor may be connected downstream. This results in a prediction gain, for example, in coding audio signals, in particular for monotype signals when, e.g., the signals of the channels only differ in their amplitudes.
In addition, it is also advantageous when the multichannel signals are decomposed into their spectral components, for example, using a filter array or a transformation, and the multichannel spectral components thus obtained are coded separately, the prediction for the spectral components of the at least two channels being performed separately. This has the advantage of allowing flexible and effective control of the predictors. If no signal components are present in a subband, or no prediction gain is achieved, the corresponding predictor can be switched off. Implementation with a plurality of lower-order predictors is often simpler than with one higher-order broad-band predictor.